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The extended theory of planned behavior considering heterogeneity under a connected vehicle environment: A case of uncontrolled non-signalized intersections

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journal contribution
posted on 25.03.2021, 15:41 by Wenjing Zhao, Mohammed Quddus, Helai Huang, Qianshan Jiang, Kui Yang, Zhongxiang Feng
© 2020 Elsevier Ltd With the emergence of connected vehicle (CV) technology, there is a doubt whether CVs can improve driver intentions and behaviors, and thus protect them from accidents with the provision of real-time information. In order to understand the possible impacts of the real-time information provided by CV technology on drivers, this paper aims to develop a model which considers the heterogeneity between drivers with the aid of the extended theory of planned behavior. At the uncontrolled non-signalized intersections, a stated preference (SP) questionnaire survey was conducted to build the dataset consisting of 1001 drivers. Based on the collected dataset, the proposed model examines the relationships between subjective norms, attitudes, risk perceptions, perceived behavioral control and driving intentions, and studies how such driving intentions are simultaneously related to driver characteristics and experiences in the CV environment. Furthermore, driver groups which are homogenous with respect to personality traits are formed, and then are employed to analyze the heterogeneity in responses to driving intentions. Four key findings are obtained when analyzing driver responses to the real-time information provided by CV technology: 1) the proposed H-ETPB model is verified with a good fitness measure; 2) irrespective to driver personality traits, attitudes and perceived behavioral control have a direct and indirect association with driving intentions to accelerate; 3) driving intentions of high-neurotic drivers to accelerate are significantly related to subjective norms, while that of low-neurotic drivers are not; 4) elder high-neurotic drivers, and low-neurotic drivers who have unstable salaries or ever joined in online car hailing service have a strong intention in accelerating. The findings of this study could provide the theoretical framework to optimize traffic performance and information design, as well as provide in-vehicle personalized information service in the CV and CAV environments and assist traffic authorities to design the most acceptable traffic rules for different drivers at an uncontrolled non-signalized intersection.

Funding

The Joint Research Scheme of National Natural Science Foundation of China/Research Grants Council of Hong Kong (No. 71561167001 & N_HKU707/15)

The National Natural Science Foundation of China (Project No. 71701216)

National Key Research and Development Plan (No. 2018YFB1201601)

History

School

  • Architecture, Building and Civil Engineering

Published in

Accident Analysis and Prevention

Volume

151

Publisher

Elsevier

Version

AM (Accepted Manuscript)

Rights holder

© Elsevier

Publisher statement

This paper was accepted for publication in the journal Accident Analysis and Preventions and the definitive published version is available at https://doi.org/10.1016/j.aap.2020.105934

Acceptance date

30/11/2020

Publication date

2021-01-11

Copyright date

2021

ISSN

0001-4575

Language

en

Depositor

Prof Mohammed Quddus . Deposit date: 16 March 2021

Article number

105934